Mining drug targets based on microarray experiments

Life science industry has been flourished with the explosion of online Bioinformatics databases and tools, which can affect the drug discovery process and development. The integration of unstructured data, available in biomedical literature (i.e. PubMED), and structured data, existing in biological databases, by applying both text and data mining techniques is a very critical issue in order to identify selected desirable genes or drug targets. The current work describes a system, drug target integrative miner (DruTiMine), which aims at providing a service to enhance and shorten the process of drug target discovery for pharmaceutical companies and research labs concerned with drug discovery. The system applies both the capabilities of text mining and data mining techniques for drug target discovery through integration of multiple biomedical resources, related to a specific disease, and mining the association among them. Furthermore, an association rule mining algorithm, multi-basket miner, has been developed in order to discover associations of categories having multiple values.